检索结果-南通市图书馆

An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

Computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid el-Shafai noha a.el-hag Ahmed Sedik Ghada.elbanby Fathi E.Abd el-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and therapy.Deep learning provides a high performance for several medical image analysis applications.This paper proposes a deep learning model for the medical image fusion process.This model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR images.Then,an additional process is executed on the extracted features.After that,the fused feature map is reconstructed to obtain the resulting fused image.Finally,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement quality.Different realistic datasets of different modalities and diseases are tested and implemented.Also,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Proposed Privacy Preservation Technique for Color Medical Images

引用

Intelligent Automation & Soft Computing 2023年第4期36卷 719-732页

作者： Walid el-Shafai Hayam A.Abd el-Hameed noha a.el-hag Ashraf A.M.Khalaf Naglaa F.Soliman Hussah Nasser AlEisa Fathi E.Abd el-Samie Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Nowadays,the security of images or information is very important.This paper introduces a proposed hybrid watermarking and encryption technique for increasing medical image security.First,the secret medical image is encrypted using Advanced Encryption Standard(AES)algorithm.Then,the secret report of the patient is embedded into the encrypted secret medical image with the Least Signiﬁcant Bit(LSB)watermarking algorithm.After that,the encrypted secret medical image with the secret report is concealed in a cover medical image,using Kekre’s Median Codebook Generation(KMCG)algorithm.Afterwards,the stego-image obtained is split into 16 parts.Finally,it is sent to the receiver.We adopt this strategy to send the secret medical image and report over a network securely.The proposed technique is assessed with different encryption quality metrics including Peak Signal-to-Noise Ratio(PSNR),Correlation Coefﬁcient(Cr),Fea-ture Similarity Index Metric(FSIM),and Structural Similarity Index Metric(SSIM).Histogram estimation is used to conﬁrm the matching between the secret medical image before and after transmission.Simulation results demonstrate that the proposed technique achieves good performance with high quality of the received medical image and clear image details in a very short processing time.

关键词： LSB steganography AES algorithm KMCG algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An Efficient CNN-Based Automated Diagnosis Framework from COVID-19 CT Images

引用

Computers, Materials & Continua 2021年第10期69卷 1323-1341页

作者： Walid el-Shafai noha a.el-hag Ghada M.el-Banby Ashraf A.M.Khalaf Naglaa F.Soliman Abeer D.Algarni Fathi E.Abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and electrical Communications Faculty of EngineeringMinia UniversityEgypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Corona Virus Disease-2019(COVID-19)continues to spread rapidly in the world.It has dramatically affected daily lives,public health,and the world economy.This paper presents a segmentation and classification framework of COVID-19 images based on deep learning.Firstly,the classification process is employed to discriminate between COVID-19,non-COVID,and pneumonia by Convolutional Neural Network(CNN).Then,the segmentation process is applied for COVID-19 and pneumonia CT images.Finally,the resulting segmented images are used to identify the infected region,whether COVID-19 or pneumonia.The proposed CNN consists of four Convolutional(Conv)layers,four batch normalization layers,and four Rectified Linear Units(RelUs).The sizes of Conv layer used filters are 8,16,32,and 64.Four maxpooling layers are employed with a stride of 2 and a 2×2 window.The classification layer comprises a Fully-Connected(FC)layer and a soft-max activation function used to take the classification decision.A novel saliencybased region detection algorithm and an active contour segmentation strategy are applied to segment COVID-19 and pneumonia CT images.The acquired findings substantiate the efficacy of the proposed framework for helping the specialists in automated diagnosis applications.

关键词： Classification segmentation COVID-19 CNN deep learning diagnosis applications

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Advances in clinical applications of bioceramics in the new regenerative medicine era

引用

World Journal of Clinical Cases 2024年第11期12卷 1863-1869页

作者： noha elshazly Fayza Eid Nasr Ayat Hamdy Safa Saied Mohamed elshazly Tissue Engineering Laboratory Faculty of DentistryAlexandria UniversityAlexandria 21526Egypt Department of Biochemistry Faculty of ScienceAlexandria UniversityAlexandria 21526Egypt Public Dental Clinic Central Administration of DentistryMinistry of Health and PopulationAlexandria 21554Egypt Department of Surgery Faculty of Veterinary MedicineAlexandria 21526Egypt

In this editorial,we comment on the hard and soft tissue applications of different ceramic-based scaffolds prepared by different mechanisms such as 3D printing,sol-gel,and electrospinning.The new concept of regenerative medicine relies on biomaterials that can trigger in situ tissue regeneration and stem cell recruitment at the defect site.A large percentage of these biomaterials is ceramic-based as they provide the essential requirements of biomaterial principles such as tailored multisize porosity,antibacterial properties,and angiogenic properties.All these previously mentioned properties put bioceramics on top of the hierarchy of biomaterials utilized to stimulate tissue regeneration in soft and hard tissue wounds.Multiple clinical applications registered the use of these materials in triggering soft tissue regeneration in healthy and diabetic patients such as bioactive glass nanofibers.The results were promising and opened new frontiers for utilizing these materials on a larger scale.The same results were mentioned when using different forms and formulas of bioceramics in hard defect regeneration.Some bioceramics were used in combination with other polymers and biological scaffolds to improve their regenerative and mechanical properties.All this progress will enable a larger scale of patients to receive such services with ease and decrease the financial burden on the government.

关键词： Regenerative medicine Bioceramics Chronic wounds Bone defects Clinical applications

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Effect of nutrition-related infodemics and social media on maternal experience: A nationwide survey in a low/middle income country

引用

World Journal of Clinical Pediatrics 2024年第1期13卷 93-106页

作者： Marwa M Zein noha Arafa Mortada H F el-Shabrawi Nehal Mohammed el-Koofy Department of Public Health and Community Medicine Cairo UniversityCairo 515211Egypt Department of Pediatric Endocrinology and Diabetes Children's HospitalKasralainy Medical SchoolCairo UniversityCairo 515211Egypt Department of Pediatrics Cairo UniversityCairo 12411Egypt Department of Pediatrics The Children's HospitalCairo UniversityCairo 12411Egypt

BACKGROUND Undernutrition is a crucial cause of morbidity and mortality among children in low-or middle-income countries(LMICs).A better understanding of maternal general healthy nutrition knowledge,as well as misbeliefs,is highly essential,especially in such settings.In the current era of infodemics,it is very strenuous for mothers to select not only the right source for maternal nutrition information but the correct information as well.AIM To assess maternal healthy nutritional knowledge and nutrition-related misbeliefs and misinformation in an LMIC,and to determine the sources of such information and their assessment methods.METHODS This cross-sectional analytical observational study enrolled 5148 randomly selected Egyptian mothers who had one or more children less than 15 years old.The data were collected through online questionnaire forms:One was for the general nutrition knowledge assessment,and the other was for the nutritional myth score.Sources of information and ways of evaluating internet sources using the Currency,Relevance,Authority,Accuracy,and Purpose test were additionally analyzed.RESULTS The mean general nutrition knowledge score was 29±9,with a percent score of 70.8%±12.1%(total score:41).The median myth score was 9(interquartile range:6,12;total score:18).The primary sources of nutrition knowledge for the enrolled mothers were social media platforms(55%).Half of the mothers managed information for currency and authority,except for considering the author's contact information.More than 60%regularly checked information for accuracy and purpose.The mothers with significant nutrition knowledge checked periodically for the author's contact information(P=0.012).The nutrition myth score was significantly lower among mothers who periodically checked the evidence of the information(P=0.016).Mothers dependent on their healthcare providers as the primary source of their general nutritional knowledge were less likely to hold myths by 13%(P=0.044).However,using social media increased the likelihood of havi

关键词： Nutrition Infodemics Maternal knowledge Myth Low/middle income country

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Protectivity of Freeze Dried Inactivated Rift Valley Fever Vaccine

引用

Open Journal of Veterinary Medicine 2024年第2期14卷 21-37页

作者： Diana M. Abulmagd Mohamed Hassan Atwa noha Ezz Aldin Marwa Yehia Hammad Taradi Abdel Fattah Said Rift Valley Fever Vaccine Research Department Veterinary Serum and Vaccine Research Institute Agriculture Research Center (ARC) Cairo Egypt

Background: Vaccinations for animals are crucial for food production, animal welfare, public health, and animal health. They are an affordable way to stop animal sickness, increase food production efficiency, and lessen or stop the spread of zoonotic diseases to humans. Animal vaccines that are both safe and efficacious are vital to modern culture. The vaccine should induce a strong, protective and prolonged immune response against the antigenic factor. In order to achieve these goals, novel vaccination techniques and an efficient adjuvant are required to render the vaccine immunogenically protective and trigger a strong immune response. Aim: Our study aims to promote and enhance the immunogenicity against RVF virus disease through lyophilized inactivated RVF vaccine through induction of early cellular, high and prolonged humeral immunity in vaccinated animals using cabopol as stabilizer and Saponin or normal saline as a diluent at time of vaccination. Moreover, manufacturing of these vaccines is easy to be done. Results: The gained results revealed that RVF freeze-dried vaccine with Carbopol that reconstituted using Saponin elicited better immune response than that reconstituted using normal saline (NaCl). The cell mediated immune response as represented by lymphocyte blastogenesis and phagocytic activity were markedly increased with high levels when we used Saponin as a diluent than that in group vaccinated with vaccine diluted with NaCl, on the other side the humeral immune response in group vaccinated using the Saponin as diluent is more detected and stayed within the protective level till the end of 11th month post vaccination (1.5 TCID50) while the immune response induced after using normal saline as a diluent stayed within the protective level till the end of 10th month post vaccination (1.8 TCID50). Conclusion: The use of Saponin as a diluent for reconstitution of the freeze dried RVF vaccine is preferable than the use of normal saline enhancing both sheep cellu

关键词： Rift Valley Fever Saponin Cabopol Binary Ethylenemine Serum Neutralization Test

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Biochemical Liver Functions and Molecular Identification of Fasciola hepatica from Experimentally Infected Rat Model

引用

Open Journal of Animal Sciences 2024年第2期14卷 88-100页

作者： Omnia M. Kandil Emad B. Ata Margarita P. Gabrashanska Hatem A. Shalaby Tamer H. Abd el-Aziz noha M. F. Hassan Soad M. Nasr Mohamed A. Helal Ebtesam M. Al-Olayan Department of Parasitology & Animal Diseases Veterinary Research Institute National Research Centre Giza Egypt Institute of Experimental Morphology Pathology and Anthropology with Museum Bulgarian Academy of Sciences Sofia Bulgaria Department of Zoology Collage of Science King Saud University Riyadh Saudi Arabia

The current study was performed to evaluate the liver function status as well as molecular characterization of the recovered worms in rats experimentally infected with F. hepatica. Sixteen male Wister rats aged 30 days were randomly allocated into two groups (n = 8). The first group was infected orally with 15 viable encysted metacercaria of F. hepatica per animal. The other group was kept non-infected (control group). At zero time (before infection), the 2nd, 4th, 6th, 8th, 10th, 12th and 14th weeks post-infection (WPI), blood and serum samples were collected via puncture of retro-orbital plexus of veins from each rat. Serum enzyme level (AST and ALT) and total protein were measured, and the serum protein profile was carried out using agarose gel electrophoresis. During the period of the experiment, serum ALT and AST activities and serum total globulins significantly increased while serum total proteins and albumin markedly decreased in the infected group. On the 14th WPI, the data of the electropherogram showed that globulin fractions (α1-, β- and γ-globulin) levels were significantly increased while α2-globulin was markedly decreased in the infected group. The molecular analysis confirmed the amplification of the ITS1, ITS2 and NDI genes of F. hepatica recovered from the infected liver of rats with amplicon sizes of 630, 510 and 560 bp, respectively. Sequencing of the amplified ITS gene resulted in the determination of 3 strains (PP108836, PP108837, and PP108838). Also, analysis of the ITS2 gene resulted in obtaining 3 isolates under the accession numbers (PP109065, PP109066, and PP109067). In conclusion, fasciolosis in the rat model is suitable for routine experimental infections and caused a pronounced liver dysfunction with discharging of the Fasciola eggs in the faeces and the development of adult stages in the bile ducts. Furthermore, molecular techniques are a sensitive tool for the identification and characterisation

关键词： Fasciola hepatica Liver Functions Serum Enzymes Serum Protein electrophoresis Molecular Characterization

来源：

维普期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

Prevelance of Bovine Cysticercosis in Egypt and the Cysticidal Effect of Two Extracts Obtained from Balanites aegyptiaca and Moringa oleifera on Mice Model Affected with T. saginata Cysticerci

引用

Open Journal of Animal Sciences 2024年第2期14卷 39-55页

作者： Omnia M. Kandil noha M. F. Hassan Doaa Sedky Hatem A. Shalaby Heba M. Ashry Nadia M. T. Abu el Ezz Sahar M. Kandeel Mohamed S. Abdelfattah L. Ying Ebtesam M. Al-Olayan Parasitology and Animal Diseases Department Veterinary Research Institute National Research Centre Dokki Cairo Egypt Chemistry of Natural Compounds Department Pharmaceutical and Drugs Industries Research Institute National Research Centre Dokki Cairo Egypt Chemistry Department Faculty of Science Helwan University Cairo Egypt State Key Laboratory of Plateau Ecology and Agriculture Qinghai University Xining China College of Agriculture and Animal Husbandry Qinghai University Xining China Department of Zoology Collage of Science King Saud University Riyadh Saudi Arabia

The aim of the present study was to determine the prevalence of bovine cysticercosis in both cattle and buffloas, in Egypt and to assess the cysticidal efficacy of Balanites aegyptiaca fruits (B. aegyptiaca) and Moringa oleifera seeds (M. oleifera) extracts in experimentally infected mice. The study detected the level of tumor necrosis factor (TNF-α) to monitor the immune and inflammatory responses of experimentally infected mice. Through meat inspection, a total number of 2125 male bovine, 2 to 5 years old, (1125 cattle and 1000 buffloes) were examined under the authority of Albsatine and Alwaraq official abattoirs in Cairo Governorate, Egypt covering the period extended from March 2022 to April 2023. The overall prevalence of the disease among bovine was 7.8% (6.31% of cattle and 9.5% of buffloes). Besides, B. aegyptiaca and M. oleifera extracts showed cysticidal activity in experimentally infected mice. A decrease in the numbers of cysticerci was found in all treated mice groups, and up to 88% reduction was achieved in the B. aegyptiaca-treated group;higher than that was recorded in both M. oleifera (72.23%) and albendazole-treated ones (80.56%). Postmortem findings proved that M. oleifera and B. aegyptiaca reduced cysticerci numbers comparable to a commercial anthelmintic. The study showed a significant decrease (P 0.001) in TNF-α levels after treatment with Balanites and Moringa extracts, compared with the untreated control and the albendazole-treated groups.

关键词： Prevalence Balanites aegyptiaca Moringa oleifera Mice T. saginata Cysticerci

来源：

维普期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

Novel Framework of Segmentation 3D MRI of Brain Tumors

引用

Computers, Materials & Continua 2023年第2期74卷 3489-3502页

作者： Ibrahim Mahmoud el-Henawy Mostafa.elbaz Zainab H.Ali noha Sakr Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazigEgypt Department of Computer Science Faculty of Computers and InformaticsKafrelsheikh UniversityKafrelsheikhEgypt Department of Embedded Network Sys.and Tec. Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Medical image segmentation is a crucial process for computer-aided diagnosis and surgery.Medical image segmentation refers to portioning the images into small,disjointed parts for simplifying the processes of analysis and examination.Rician and speckle noise are different types of noise in magnetic resonance imaging(MRI)that affect the accuracy of the segmentation process negatively.Therefore,image enhancement has a significant role in MRI segmentation.This paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free image.The proposed techniques consider the values of Peak Signal to Noise Ratio(PSNR)and the level of noise as inputs to the attention-U-Net model for segmentation of the tumor.The framework has been divided into three stages:removing speckle and Rician noise,the segmentation stage,and the feature extraction stage.The framework presents solutions for each problem at a different stage of the segmentation.In the first stage,the framework uses Vibrational Mode Decomposition(VMD)along with Block-matching and 3D filtering(Bm3D)algorithms to remove the Rician.Afterwards,the most significant Rician noise-free images are passed to the three different methods:Deep Residual Network(DeRNet),Dilated Convolution Auto-encoder Denoising Network(Di-Conv-AE-Net),andDenoising Generative Adversarial Network(DGAN-Net)for removing the speckle noise.VMDand Bm3D have achieved PSNR values for levels of noise(0,0.25,0.5,0.75)for reducing the Rician noise by(35.243,32.135,28.214,24.124)and(36.11,31.212,26.215,24.123)respectively.The framework also achieved PSNR values for removing the speckle noise process for each level as follows:(34.146,30.313,28.125,24.001),(33.112,29.103,27.110,24.194),and(32.113,28.017,26.193,23.121)forDeRNet,Di-Conv-AE-Net,and DGAN-Net,respectively.The experiments that have been conducted have proved the efficiency of the proposed framework against classical filters such as Bilateral,Frost

关键词： MRI Rician noise speckle noise segmentation deep learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Enhancing Task Assignment in Crowdsensing Systems Based on Sensing Intervals and Location

引用

Computers, Materials & Continua 2022年第6期71卷 5619-5638页

作者： Rasha Sleem Nagham Mekky Shaker el-Sappagh Louai Alarabi noha AHikal Mohammed elmogy Faculty of Computers and Information Mansoura UniversityMansoura35516Egypt Faculty of Computers and Artificial Intelligence Benha UniversityBanha13518Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt College of Computer and Information Systems Umm Al-Qura UniversityMecca715Saudi Arabia

The popularity of mobile devices with sensors is captivating the attention of researchers to modern techniques,such as the internet of things(IoT)and mobile crowdsensing(MCS).The core concept behind MCS is to use the power of mobile sensors to accomplish a difficult task collaboratively,with each mobile user completing much simpler micro-tasks.This paper discusses the task assignment problem in mobile crowdsensing,which is dependent on sensing time and path planning with the constraints of participant tra.el distance budgets and sensing time intervals.The goal is to minimize aggregate sensing time for mobile users,which reduces energy consumption to encourage more participants to engage in sensing activities and maximize total task quality.This paper introduces a two-phase task assignment framework called location time-based algorithm(LTBA).LTBA is a framework that enhances task assignment in MCS,whereas assigning tasks requires overlapping time intervals between tasks and mobile users’tasks and the location of tasks and mobile users’paths.The process of assigning the nearest task to the mobile user’s current path depends on the ant colony optimization algorithm(ACO)and Euclidean distance.LTBA combines two algorithms:(1)greedy online allocation algorithm and(2)bio-inspired tra.eldistance-balance-based algorithm(B-DBA).The greedy algorithm was sensing time interval-based and worked on reducing the overall sensing time of the mobile user.B-DBA was location-based and worked on maximizing total task quality.The results demonstrate that the average task quality is 0.8158,0.7093,and 0.7733 for LTBA,B-DBA,and greedy,respectively.The sensing time was reduced to 644,1782,and 685 time units for LTBA,B-DBA,and greedy,respectively.Combining the algorithms improves task assignment in MCS for both total task quality and sensing time.The results demonstrate that combining the two algorithms in LTBA is the best performance for total task quality and total sensing time,and the greedy algorithm follows it then B-DBA.

关键词： Mobile crowdsensing online task assignment participatory sensing path planning sensing time intervals ant colony optimization

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：